MétaCan
Menu
Back to cohort
Record W4392536384 · doi:10.5336/nurses.2023-97408

The Relationship Between Nomophobia and Alexithymia in Nurse Interns: Descriptive Study

2024· article· en· W4392536384 on OpenAlexaboutno aff
Huri Melek AKIN, Hatice Durmaz

Bibliographic record

VenueTurkiye Klinikleri Journal of Nursing Sciences · 2024
Typearticle
Languageen
FieldPsychology
TopicWorkaholism, burnout, and well-being
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaDescriptive researchPsychologyDescriptive statisticsMedicineClinical psychologySociologySocial science

Abstract

fetched live from OpenAlex

Objective: The aim of the study is to examine the relationship between nomophobia and alexithymia in intern nursing students. Material and Methods: The universe of the research consisted of intern students of Atatürk University Nursing Faculty (n=250). The sample of the study consisted of students who used smart phones and volunteered to participate in the research (n=207). Post hoc power analysis was performed to determine the adequacy of the sample size of the study. In the power analysis, it was determined that the power of the study was 0.99 at the significance level of 0.05 and at the 95% confidence interval. Sociodemographic Data Form, Nomophobia Scale and Toronto Alexithymia Scale were used in the study. Data analysis was done with SPSS program. Results: It was found that of the students on the Nomophobia Scale mean score was 69.55±27.74; the Toronto Alexithymia Scale mean score was 51.12±11.15 It was determined that 44% of the students had moderate nomophobia, 15% had extreme nomophobia, and 28% had alexithymia. As a result of the research, it was determined that there was a positive and significant correlation between the mean scores of the Nomophobia Scale and the Alexithymia Scale (p<0.05). Conclusion: It was determined that the students had moderate nomophobia and alexithymia and they affected each other. As the level of nomophobia of the students increases, the level of alexithymia also increases.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.108
Threshold uncertainty score0.495

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.107
GPT teacher head0.418
Teacher spread0.312 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueTurkiye Klinikleri Journal of Nursing SciencesSame topicWorkaholism, burnout, and well-beingFrench-language works237,207